NVIDIA RTX PCs and DGX Spark systems are ideal for running Hermes Agent, an open-source agentic framework that has gained significant traction. Developed by Nous Research, Hermes Agent has surpassed 140,000 GitHub stars in under three months and is currently the most used agent globally, according to OpenRouter. The framework is designed for reliability and self-improvement, with features that make it provider- and model-agnostic. Hermes Agent can integrate with messaging apps, access local files and applications, and operate 24/7.
Four key capabilities set it apart: self-evolving skills, contained sub-agents, reliability by design, and better results with the same model. Developers using identical models across frameworks consistently report stronger results with Hermes due to its active orchestration layer, which enables persistent, on-device agents instead of task-by-task execution. Both the Hermes agent and the underlying LLM are built to run locally, meaning the quality of hardware directly impacts user experience. NVIDIA RTX GPUs are purpose-built for this type of workload.
Qwen 3.6, a new series of high-performance, open-weight large language models from Alibaba, are ideal for running local agents like Hermes. The Qwen 3.6 27B and 35B parameter models outperform their previous-generation 120B and 400B parameter counterparts and run on NVIDIA RTX and DGX Spark for accelerated agentic AI. NVIDIA Tensor Cores accelerate AI inference, delivering higher throughput and lower latency, allowing Hermes to handle multistep tasks or refine its skills in seconds. DGX Spark, a compact, efficient standalone machine, is ideal for sustained agentic workflows with 128GB of unified memory and 1 petaflop of AI performance. The new Qwen 3.6 35B model delivers equivalent intelligence in a leaner footprint, running faster and enabling concurrent workloads.
To maximize performance and ease of use, read the Hermes DGX Spark playbook.
Source: nvidia
